Computer programming generally refers to a manual process where humans provide instructions to a machine for processing and execution. For example, computer programmers enter source code written in a computer programming language into a source code editor or integrated development environment (IDE). A compiler transforms or “compiles” the source code into a lower-level machine-readable language, such as assembly language or machine code, for execution by a machine. Additionally, some compilers may compile source code into an intermediate language for execution by an interpreter computer program of a runtime environment.
Automated source code generation refers to the process of automatically creating source code from visual elements placed in a graphical user interface (GUI) builder, using input provided to a wizard program, programmatically, or based on templates written in a custom format other than the computer language of source code that is to be generated. However, such methods of automated source code generation suffer from various deficiencies. For instance, GUI builders and wizard-based source code generators produce a limited amount of non-operational “starter” source code (e.g., outlines, skeletons, or stubs). Computer programmers then apply a significant amount of manual effort to augment the small amount of generated source code to create a functioning software application. In addition, programmatic source code generation is complex, cumbersome, and prone to high-level syntactic errors.
Template-based source code generators use custom syntax and formatting that introduces increased complexity for computer programmers. For example, template-based solutions involve a proprietary validator to check and flag errors in the custom syntax and formatting of associated templates. However, these proprietary validators are unable to detect syntactical errors present in computer language source code that is to be generated from a template. Therefore, most errors present in source code generated from custom templates are detected after source code already has been generated from a template. As a result, computer programmers perform the tedious and time-consuming tasks of repetitively modifying a template and regenerating the same desired source code until the generated source code successfully compiles and executes in the target computer language. Accordingly, providing new, improved, and more accurate ways of generating source code is of importance.